Genome-scale predictions of how microbes control their metabolic activity are rapidly improving in accuracy, largely owing to the development of mathematical models, which combine genomic and biochemical knowledge with efficient optimization algorithms.
Yet, some of the most fundamental properties of real microbial ecosystems crucially depend on aspects that are beyond the metabolic networks of individual species, such as metabolite-mediated interactions between different microbes and spatio-temporal variation of environmental conditions. Can current models account for such effects, and help understand the dynamics and evolution of complex microbial communities? We explore possible answers to this question, with applications ranging from "synthetic ecology" to the organization of the human microbiome.
